AIMC Topic: Humans

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Challenges for future directions for artificial intelligence integrated nursing simulation education.

Korean journal of women health nursing
Artificial intelligence (AI) has tremendous potential to change the way we train future health professionals. Although AI can provide improved realism, engagement, and personalization in nursing simulations, it is also important to address any issues...

A Deep Learning Approach for Neuronal Cell Body Segmentation in Neurons Expressing GCaMP Using a Swin Transformer.

eNeuro
Neuronal cell body analysis is crucial for quantifying changes in neuronal sizes under different physiological and pathologic conditions. Neuronal cell body detection and segmentation mainly rely on manual or pseudo-manual annotations. Manual annotat...

Comprehensive scientometrics and visualization study profiles lymphoma metabolism and identifies its significant research signatures.

Frontiers in endocrinology
BACKGROUND: There is a wealth of poorly utilized unstructured data on lymphoma metabolism, and scientometrics and visualization study could serve as a robust tool to address this issue. Hence, it was implemented.

Extrapolation of affective norms using transformer-based neural networks and its application to experimental stimuli selection.

Behavior research methods
Data on the emotionality of words is important for the selection of experimental stimuli and sentiment analysis on large bodies of text. While norms for valence and arousal have been thoroughly collected in English, most languages do not have access ...

Imaging biomarkers and radiomics in pediatric oncology: a view from the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project.

Pediatric radiology
This review paper presents the practical development of imaging biomarkers in the scope of the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project, as a n...

Assessing the accuracy and completeness of artificial intelligence language models in providing information on methotrexate use.

Rheumatology international
We aimed to assess Large Language Models (LLMs)-ChatGPT 3.5-4, BARD, and Bing-in their accuracy and completeness when answering Methotrexate (MTX) related questions for treating rheumatoid arthritis. We employed 23 questions from an earlier study rel...

Behind the mask: a critical perspective on the ethical, moral, and legal implications of AI in ophthalmology.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: This narrative review aims to provide an overview of the dangers, controversial aspects, and implications of artificial intelligence (AI) use in ophthalmology and other medical-related fields.

Beam mask and sliding window-facilitated deep learning-based accurate and efficient dose prediction for pencil beam scanning proton therapy.

Medical physics
BACKGROUND: Accurate and efficient dose calculation is essential for on-line adaptive planning in proton therapy. Deep learning (DL) has shown promising dose prediction results in photon therapy. However, there is a scarcity of DL-based dose predicti...

Safety and Accuracy of Robot-Assisted Cervical Screw Placement: A Systematic Review and Meta-Analysis.

World neurosurgery
OBJECTIVE: The purpose of this study was to compare the accuracy and safety of robot-assisted (RA) cervical screw placement with conventional freehand (FH) technique.

Automatic dose prediction using deep learning and plan optimization with finite-element control for intensity modulated radiation therapy.

Medical physics
BACKGROUND: Automatic solutions for generating radiotherapy treatment plans using deep learning (DL) have been investigated by mimicking the voxel's dose. However, plan optimization using voxel-dose features has not been extensively studied.